The rapid growth of Indonesian online news articles presents challenges in clustering based on content similarity. This study aims to develop a clustering system for online news articles using the k-medoids method. A total of 500 articles from Kaggle were processed through text preprocessing (case folding, tokenizing, stopword removal, and stemming), TF-IDF weighting, and clustering with k-medo…